About Xorvelima
We build the risk layer that sits underneath automated crypto portfolios — translating market volatility into clear, actionable protection.
Why we exist
Xorvelima was founded on a simple observation: most crypto portfolio tools are built to chase performance, not to manage downside. Automated strategies can move faster than any human reviewer, but speed without a disciplined risk framework just means mistakes happen faster too.
We set out to build the missing piece — a predictive risk layer that works alongside AI-managed portfolios, continuously modelling exposure and triggering protective action before losses compound.
That focus has stayed the same since the beginning: fewer dashboards to babysit, clearer signals, and stop-loss logic that behaves consistently even when markets don't.
Risk modelling is a continuous process, not a one-time setup.
What we value
These principles shape every model, alert, and feature decision we make.
Protection before performance
Our models are designed first to limit downside, not to chase short-term upside. Capital preservation is treated as the primary objective, not an afterthought.
Transparent logic
Every stop-loss trigger and risk score is traceable. We avoid black-box outputs that users can't interpret or question.
Continuous recalibration
Markets shift, and so do our models. Risk thresholds are reviewed and adjusted on an ongoing basis rather than set once and left alone.
Plain-language communication
Risk reporting should be understandable without a finance degree. We prioritise clarity over jargon in every alert and summary.
How we work
A small, focused team structure built around the stages of risk management rather than departments.
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Modelling
Builds and refines the predictive logic behind risk scoring and threshold alerts.
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Monitoring
Oversees live portfolio signals and ensures protective triggers behave as intended.
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Platform
Maintains the dashboard, integrations, and the reliability of the system end to end.
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Support
Helps users understand their risk settings and interpret what the system is reporting.
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Compliance
Reviews disclosures and ensures our communication stays accurate and measured.
Where we're headed
Our roadmap stays centred on one question: does this make risk easier to see and act on?
As crypto markets evolve, so will the inputs our models rely on. We expect to keep refining prediction accuracy, expanding the range of risk signals we surface, and simplifying how that information reaches the people using Xorvelima day to day — without drifting from the core focus on downside protection.
Cryptoasset investments carry a high degree of risk. Historical modelling accuracy does not guarantee future results, and automated stop-loss mechanisms cannot eliminate market risk entirely.